Snr Manager Applied Science (OCI/GenAI)

Oracle Cloud Infrastructure (OCI) is at the forefront of cloud innovation, blending the agility of a startup with the reliability of a leading enterprise software provider.

Our AI Science team

Sr. Manager, Applied Science (M3)

to lead a high-impact applied science team within OCI. In this role, you will drive the development of secure, scalable, and innovative AI solutions leveraging cutting-edge techniques in computer vision, Large multimodal models and other GenAI technologies.

Key Responsibilities

Applied Research & Development

Lead a team of applied scientists and data engineers to research, prototype, and productize computer vision and generative AI solutions for image

/video data

Evaluate and integrate emerging technologies such as LLMs, LMMs, and diffusion models into production-grade services.

ML Solution Design

Translate business and functional requirements into robust machine learning requirements.

Architect, develop, train, and fine-tune ML models for performance, scalability, and real-time processing.

Cross-functional Collaboration

Partner closely with product managers, engineering leads, and annotation/data teams to align on priorities, define requirements, and deliver end-

to-end AI capabilities.

Foster a collaborative and innovative team culture that bridges science, product, and engineering needs.

Product Innovation

Drive the transformation of scientific advancements into marketable AI-driven services.

Ensure solutions are competitive, customer-focused, and aligned with OCI’s strategic vision.

Data Analytics & Insights

Leverage large-scale data to generate actionable insights and inform model development, evaluation, and continuous improvement.

Quality, Security & IP

Champion best practices for testing, benchmarking, and model validation to ensure reliability and performance.

Identify and lead efforts in intellectual property creation, including patents and publications.

Preferred Qualifications

Ph.D.

Expertise in GenAI, LLMs, LMMs, object detection, facial recognition, and image classification.

deep learning architectures

Demonstrated ability to build and scale ML pipelines and AI services in production environments.

leadership Experience

Excellent communication skills, including the ability to clearly explain complex technical concepts to both technical and non-technical stakeholders.

business acumen

with the ability to align technical initiatives to broader business goals.

fast-paced, evolving environments